[1] FEUERRIEGEL S, HARTMANN J, JANIESCH C, et al. Generative AI[J]. Business & information systems engineering, 2024, 66(1): 111-126.
[2] 中国 网. 政府 工作 报告( 全文 ) [EB/OL]. [2025-09- 05]. http://www.china.com.cn/lianghui/news/2025-03/12/ content_117762844.shtml. (China internet information center. Report on the work of the government[EB/OL]. [2025-09- 05]. http://www.china.com.cn/lianghui/news/2025-03/12/ content_117762844.shtml.)
[3] AI Q, ZHAN J, LIU Y. Foundations of GenIR[EB/OL]. [2025- 09-26]. http://arxiv.org/abs/2501.02842.
[4] CNNIC. 生成 式人 工智 能应 用发 展报 告( 2024) [R]. 中国 互联 网络 信息 中心, 2024. (CNNIC. Generative Artificial Intelligence Application Development Report (2024) [R]. Information Center of the China Internet Network, 2024.)
[5] NOY S, ZHANG W. Experimental evidence on the productivity effects of generative artificial intelligence[J]. Science, 2023, 381(6654): 187-192.
[6] SUN X, MA R, ZHAO X, et al. Trusting the search: unraveling human trust in health information from Google and ChatGPT[EB/ OL]. [2024-09-21]. http://arxiv.org/abs/2403.09987.
[7] KRUPP L, STEINERT S, KIEFER-EMMANOUILIDIS M, et al. Unreflected Acceptance—Investigating the Negative Consequences of ChatGPT-Assisted Problem Solving in Physics Education[EB/OL]. [2025-09-09]. http://arxiv.org/ abs/2309.03087.
[8] WANG P. The rationality of explanation or human capacity? understanding the impact of explainable artificial intelligence on human-AI trust and decision performance[J]. Information processing and management, 2024, 61(4): 103732.
[9] 邓俊, 易欣妍, 傅诗婷. 社交机器人如何提升用户社会临场感?表情包情感效价在人智对话交互中的作用[J]. 图书 情报 知识, 2023, 40(2): 29-39. (DENG J, YI X Y, FU S T. How to improve users social presence by social robots? the role of sticker’s emotional valence in Human-AI conversation interaction[J]. Documentation, information & knowledge, 2023, 40(2): 29-39.)
[10] INKPEN K, CHAPPIDI S, MALLARI K, et al. Advancing Human-AI complementarity: the impact of user expertise and algorithmic tuning on joint decision making[J]. ACM transactions on computer-human interaction, 2023, 30(5): 1-29.
[11] WEI XIONG, CHEN WANG, LIANG MA. Partner or subordinate? sequential risky decision-making behaviors under human-machine collaboration contexts[J]. Computers in human behavior, 2023, 139: 107556.
[12] 王俊, 谢青伶, 刘畅. 日常生活情境下用户与生成式人工智能交互行为分析[J]. 图书情报知识, 2025, 42(2): 60-69, 93. (WANG J, XIE Q L, LIU C. User’s interaction behavior with generative artificial intelligence in daily life contexts[J]. Documentation, information & knowledge, 2025, 42(2): 60-69, 93.)
[13] SEBASTIAN WANDELT, XIAOQIAN SUN, ANMING ZHANG. AI-driven assistants for education and research? a case study on ChatGPT for air transport management[J]. Journal of air transport management, 2023, 113(C): 102483.
[14] 王若佳, 范科鸣, 刘智锋, 等. 生成式人工智能环境下用户信息检索式行为研究[J]. 数据分析与知识发现, 2024, 8(Z1): 20-30. (WANG R J, FAN K M, LIU Z F, et al. A Study on user querying behavior in generative artificial intelligence environment[J]. Data analysis and knowledge discovery, 2024, 8(8/9): 20-30.)
[15] 宋小康, 赵宇翔, 宋士杰, 等. 社会技术系统范式下AI赋能的替代信息搜索:特征、理论框架与研究展望[J]. 图书情报知识, 2023, 40(4): 111-121. (SONG X K, ZHAO Y X, SONG S J, et al. The features, theoretical framework and research prospects of ai-enabled surrogate information searching: a sociotechnical system paradigm[J]. Documentation, information & knowledge, 2023, 40(4): 111-121.)
[16] 冷旭, 陈渝. 替代信息搜索情境下的用户转移意愿研究[J]. 情报杂志, 2024, 43(12): 186-197. (LENG X, CHEN Y. Users’ switching intention in surrogate information searching context[J]. Journal of intelligence, 2024, 43(12): 186-197.)
[17] 周涛, 吴晓颖, 邓胜利. 用户知识问答转移行为研究:从问答社区到生成式AI[J]. 情报杂志, 2024, 43(2): 200-207. (ZHOU T, WU X Y, DENG S L. Examining users’s witching behavior of knowledge Q&A: from Q&A communities to GenerativeAI[J]. Journal of intelligence, 2024, 43(2): 200-207.)
[18] 李阳, 孙建军. 大模型对情报学发展的影响思考[J]. 情报学 报, 2025, 44(2): 246-256. (LI Y, SUN J J. Reflections on the impact of large language models on the development of information science[J]. Journal of the China Society for Scientific and Technical Information, 2025, 44(2): 246-256.)
[19] LI X, JIN J, ZHOU Y, et al. From matching to generation: A survey on generative information retrieval[J]. ACM transactions on information systems, 2025, 43(3): 1-62.
[20] XIAOYUE MA A B, YUDI HUO. Drawing a satisfying picture: an exploratory study of human-AI interaction in AI painting through breakdown–repair communication strategies[J]. Information processing & management, 2024, 61(4): 103755.
[21] 孙榕, 李白杨. 生成式人工智能(GAI)背景下的新型数字鸿沟识别框架研究[J]. 图书情报知识, 2025, 42(3): 19-30. (SUN R, LI B Y. A framework for identifying the new digital divide within the context of generative artificial intelligence(GAI)[J]. Documentation, information & knowledge, 2025, 42(3): 19-30.)
[22] 张铮, 刘晨旭. 大模型幻觉:人机传播中的认知风险与共治可能[J]. 苏州大学学报(哲学社会科学版), 2024, 45(5): 171- 180. (ZHANG Z, LIU C X. The hallucinations of large language models: perceived risk and the possibility of Co-governance in Human-computer Communication[J]. Journal of Soochow University(philosophy & social science edition), 2024, 45(5): 171-180.)
[23] 吴丹, 孙国烨. 生成式智能搜索结果可信度研究[J]. 中国图书馆学报, 2023, 49(6): 51-67. (WU D, SUN G Y. The Credibility of the results of generative intelligent search[J]. Journal of library science in China, 2023, 49(6): 51-67.)
[24] 宋士杰, 赵宇翔, 朱庆华. 从ELIZA到ChatGPT:人智交互体验中的AI生成内容( AIGC)可信度评价[J]. 情报资料工作, 2023, 44(4): 35-42. (SONG S J, ZHAO Y X, ZHU Q H. From ELIZA to ChatGPT: AI-Generated content (AIGC) credibility evaluation in human-intelligent interactive experience[J]. Information and documentation services, 2023, 44(4): 35-42.)
[25] 王一博, 郭鑫, 刘智锋, 等. AI生成与学者撰写中文论文摘要的检测与差异性比较研究[J]. 情报杂志, 2023, 42(9): 127-134. (WANG Y B, GUO X, LIU Z F, et al. Detection and comparative study of differences between AI-Generated and scholar-written Chinese abstracts[J]. Journal of intelligence, 2023, 42(9): 127- 134.)
[26] JIMPEI HITSUWARI, YOSHIYUKI UEDA, WOOJIN YUN, et al. Does human–AI collaboration lead to more creative art? aesthetic evaluation of human-made and AI-generated haiku poetry[J]. Computers in human behavior, 2023, 139(C): 107502.
[27] UWE MESSER. Co-creating art with generative artificial intelligence: implications for artworks and artists[J]. Computers in human behavior: artificial humans, 2024, 2(1): 100056.
[28] ALAVI M, LEIDNER D, MOUSAVI R. Knowledge Management Perspective of Generative Artificial Intelligence (GenAI)[EB/ OL]. [2025-09-22]. https://papers.ssrn.com/abstract=4782875.
[29] 徐娟, 黄奇, 袁勤俭. 社会认知理论及其在信息系统研究中的应用与展望[J]. 现代情报, 2020, 40(6): 145-153. (XU J, HUANG Q, YUAN Q J. Social cognition theory and its application and prospect in the field of information system research[J]. Journal of modern information, 2020, 40(6): 145-153.)
[30] 李爱霞. 基于学习行为数据的认知特性刻画研究[D]. 上海: 华东师范大学, 2021. (LI A X. Research on characterization of cognitive features based on learning behavior data[D]. Shanghai: East China Normal University, 2021.)
[31] 林鑫, 周知. 用户认知对标签使用行为的影响分析—— 基于电影社会化标注数据的实证分析[J]. 情报理论与实践, 2015, 38(10): 85-88. (LIN X, ZHOU Z. Analysis of the influence of user cognition on tag use behavior[J]. Information studies: theory & application, 2015, 38(10): 85-88.)
[32] 周涛, 张春雷, 邓胜利. 基于C-A-C的生成式AI用户间歇性中辍行为研究[J]. 现代情报, 2025, 45(3): 40-50, 64. (ZHOU T, ZHANG C L, DENG S L. Research on Generative AI users’ intermittent discontinuance based on the C-A-C[J]. Journal of modern information, 2025, 45(3): 40-50, 64.)
[33] MEIER M, MAIER C, THATCHER J B, et al. Chatbot interactions: how consumption values and disruptive situations influence customers’ willingness to interact[J]. Information systems journal, 2024, 34(5): 1579-1625.
[34] 孙林辉, 杨露, 袁晓芳, 等. 基于场独立/ 场依存认知风格的消费者信息搜寻效率研究[J]. 情报理论与实践, 2023, 46(4): 122-130. (SUN L H, YANG L, YUAN X F, et al. Research on information search efficiency of consumers based on their cognitive style of field-independence / field-dependence[J]. Information studies:theory & application, 2023, 46(4): 122-130.)
[35] 孙晓宁, 姚青. 信息搜索用户学习行为投入影响研究:基于认知风格与自我效能[J]. 情报理论与实践, 2020, 43(10): 99-107. (SUN X N, YAO Q. An exploration of factors related to learning behavioral engagement on information search users: based on cognitive style and self-efficacy [J]. Information studies: theory & application, 2020, 43(10): 99-107.)
[36] 郭海玲, 宋佳琳. 社会认知视角下移动端视频用户学习型搜索行为的影响研究[J]. 情报资料工作, 2022, 43(3): 75- 83. (GUO H L, SONG J L. Research on the influence of mobile video users’ learning search behavior from the perspective of social cognition[J]. Information and documentation services, 2022, 43(3): 75-83.)
[37] PINSKI M, BENLIAN A. AI literacy for users – a comprehensive review and future research directions of learning methods, components, and effects[J]. Computers in human behavior: artificial humans, 2024, 2(1): 100062.
[38] WANG B, RAU P L P, YUAN T. Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale[J]. Behaviour & information technology, 2023, 42(9): 1324-1337.
[39] CAROLUS A, KOCH M J, STRAKA S, et al. MAILS - Meta AI literacy scale: development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change- and meta-competencies[J]. Computers in human behavior: artificial humans, 2023, 1(2): 100014.
[40] 周琼, 徐亚苹, 蔡迎春. 高校学生人工智能素养能力现状及影响因素多维分析[J]. 图书情报知识, 2024, 41(3): 38- 48. (ZHOU Q, XU Y P, CAI Y C. An examination of ai literacy among university students: current status and multifaceted influencing factors[J]. Documentation, information & knowledge, 2024, 41(3): 38-48.)
[41] CELIK I. Exploring the determinants of artificial intelligence (AI) literacy: digital divide, computational thinking, cognitive absorption[J]. Telematics and informatics, 2023, 83(C): 102026.
[42] TSENG Y J, XIAO R, BOGART C, et al. Assessing the efficacy of goal-based scenarios in scaling AI literacy for non-technical learners[C]//Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2. New York, USA: Association for Computing Machinery, 2024: 1842-1843.
[43] CHEN G, FAN J, AZAM M. Exploring artificial intelligence (AI) chatbots adoption among research scholars using unified theory of acceptance and use of technology (UTAUT) [EB/OL]. [2025-09-22]. https://journals.sagepub.com/ doi/10.1177/09610006241269189.
[44] 赵宇翔, 景雨田, 宋士杰, 等. AIGC赋能的提示素养:生成式ai时代的人智交互能力重构[J]. 情报资料工作, 2025, 46(3): 14-25. (ZHAO Y X, JING Y T, SONG S J, et al. Prompt literacy for AIGC empowerment: reconstructing Human-AI interaction capabilities in the generative AI era[J]. Information and documentation services, 2025, 46(3): 14-25.)
[45] 杜瑾. 美国高校图书馆人工智能素养教育服务实践研究及其启示[J]. 图书情报工作, 2025, 69(14): 135-148. (DU J. Research on the artificial intelligence literacy education services in American university libraries and its implications[J]. Library and information service, 2025, 69(14): 135-148.)
[46] KOLB D. Experiential learning: experience as the source of learning and development[M]// London: Pearson Education, 2014.
[47] KOLB A, KOLB D. The Kolb learning style inventory—version 3.12005 technical specifications[S/OL]. [2025-09-06]. https:// www.researchgate.net/publication/241157771_The_Kolb_ Learning_Style_Inventory-Version_31_2005_Technical_Specifi_ cations.
[48] MAYA J, LUESIA J F, PÉREZ-PADILLA J. The relationship between learning styles and academic performance: consistency among multiple assessment methods in psychology and education students[J]. Sustainability, 2021, 13(6): 3341.
[49] 孙晓宁, 季馥春, 刘思琦. 信息搜索用户的学习投入影响研究:基于Kolb学习风格与认知弹性理论[J]. 情报学报, 2023, 42(1): 90-102. (SUN X N, JI F C, LIU S Q. Research on the learning engagement of information search users: based on Kolb’s learning style and cognitive flexibility theory[J]. Journal of the China Society for Scientific and Technical Information, 2023, 42(1): 90-102.)
[50] HALTTUNEN K. Students’ conceptions of information retrieval: Implications for the design of learning environments[J]. Library & information science research, 2003, 25(3): 307-332.
[51] SHAW R S. A study of the relationships among learning styles, participation types, and performance in programming language learning supported by online forums[J]. Computers & education, 2012, 58(1): 111-120.
[52] SPATHARIOTI S E, ROTHSCHILD D M, GOLDSTEIN D G, et al. Comparing traditional and LLM-based search for consumer choice: a randomized experiment[EB/OL]. [2025-09-07]. https:// arxiv.org/abs/2307.03744v2.
[53] ZHENG J, WONG K C, ZHOU J, et al. Large language model in ideation for product innovation: an exploratory comparative study[EB/OL]. [2025-09-29]. https://papers.ssrn.com/ abstract=4729982.
[54] XU R, FENG Y, CHEN H. ChatGPT vs. Google: A comparative study of search performance and user experience[EB/OL]. [2025- 09-28]. http://arxiv.org/abs/2307.01135.
[55] SHARMA N, LIAO Q V, XIAO Z. Generative echo chamber? effects of LLM-Powered search systems on diverse information seeking[EB/OL]. [2025-09-21]. http://arxiv.org/abs/2402.05880.
[56] 李丹丹, 朱晶晶, 甘利人. 国外网络用户认知实验研究[J]. 图书情报工作, 2009, 53(24): 69-73. (LI D D, ZHU J J, GAN L R. A review of cognitive experimental research on foreign network users[J]. Library and information service, 2009, 53(24): 69-73.)
[57] WANG B, RAU P L P, YUAN T. Measuring user competence in using artificial intelligence: validity and reliability of 2293-2303.
[63] YU R, XU X, PENG S. The impact of individual AI proficiency on human–agent collaboration: higher sensitivity to discern the comprehension ability of intelligent agents for users with higher AI proficiency levels[J]. International journal of industrial ergonomics, 2025, 107: 103745.
[64] 陈琦, 刘儒德. 当代教育心理学: 第3 版[M]. 北京: 北京师 范大 学出 版, 2019. (CHEN Q, LIU R D. Contemporary Psychology of Education [M]. Beijing: Beijing Normal University Press, 2019.)
[65] 周晓美, 谷桂芳, 尹雪燕. 新护士基于学习风格的规范化培训效果评价[J]. 护理学杂志, 2024, 39(7): 1-4. (ZHOU X M, GU G F, YIN X Y. Effect evaluation of standardized training for new nurses based on learning style [J]. Journal of nursing science, 2024, 39(7): 1-4) artificial intelligence literacy scale[J]. Behaviour & information technology, 2023, 42(9): 1324-1337.
[58] 程子佳, 陈翀. 面向流行性疾病科普的用户问题理解与答案内容组织[J]. 数据分析与知识发现, 2022, 6(2-3): 202-211. (CHENG Z J, CHEN C. Question comprehension and answer organization for scientific education of epidemics[J]. Data analysis and knowledge discovery, 2022, 6(2-3): 202-211.)
[59] TANG M, HOFREITER S, WERNER C H, et al. “who” is the best creative thinking partner? an experimental investigation of Human–Human, Human–Internet, and Human–AI CoCreation[J]. The Journal of creative behavior, 2025, 59: e1519.
[60] 宋筱璇, 刘畅. 搜索前后用户知识水平的评估及其变化情况分析[J]. 图书情报工作, 2018, 62(2): 108-116. (SONG X X, LIU C. Assessment of user knowledge level before and after searching[J]. Library and information service, 2018, 62(2): 108- 116.)
[61] FULBRIGHT R, MORRISON M. Does using ChatGPT result in human cognitive augmentation?[C]//International conference on human-computer interaction. Cham: Springer, 2024: 133-146.
[62] VACCARO M, ALMAATOUQ A, MALONE T. When combinations of humans and AI are useful: a systematic review and meta-analysis[J]. Nature human behaviour, 2024, 8(12):2293-2303.
[63] YU R, XU X, PENG S. The impact of individual AI proficiency on human–agent collaboration: higher sensitivity to discern the comprehension ability of intelligent agents for users with higher AI proficiency levels[J]. International journal of industrial ergonomics, 2025, 107: 103745.
[64] 陈琦, 刘儒德. 当代教育心理学: 第3 版[M]. 北京: 北京师 范大 学出 版, 2019. (CHEN Q, LIU R D. Contemporary Psychology of Education [M]. Beijing: Beijing Normal University Press, 2019.)
[65] 周晓美, 谷桂芳, 尹雪燕. 新护士基于学习风格的规范化培训效果评价[J]. 护理学杂志, 2024, 39(7): 1-4. (ZHOU X M, GU G F, YIN X Y. Effect evaluation of standardized training for new nurses based on learning style [J]. Journal of nursing science, 2024, 39(7): 1-4)